The massive digital transformation was escalating due to the emergence of the Covid-19 Pandemic occurred in almost all industrial sectors including the banking sector. To respond to this challenge, banking presents an innovation that is Mobile Banking. However, using Mobile Banking services in the community is considered not optimal. The data obtained from the Financial Inclusion Insight shows that only 32.2% of adults know about electronic money and Digital Banking. Due to the lack of utilization of Mobile Banking in the midst of the onslaught of essential digital transformation, it is interesting to know what indicators trigger people to be interested in using Mobile Banking. This study employs the Unified Theory of Acceptance and Use of Technology Model to analyze the factors that drive the intention of the students of IAIN Fattahul Muluk Papua to use Mobile Banking. This study is explanatory quantitative research and the type of data used is primary data obtained from the distributed questionnaires that use the Likert scale. The method used to take the samples is the Proportionate Stratified Random Sampling technique and the number of respondents is 100 students of IAIN Fattahul Muluk Papua who use Mobile Banking. The data analysis method used in this study is multiple linear regression using the SPSS 24 version application. This study uses 4 main constructs of the UTAUT Model, namely Performance Expectations, Effort Expectations, Social Influences, and Facilitating Conditions to determine their influence on the Behavioral Interests of the students of IAIN Fattahul Muluk Papua in using the Mobile Banking application. The results of this study indicate that partially Effort Expectations and Facilitating Conditions have a significant influence on Behavioral Interest with the results of each t count is greater than the t table that is 2.851>1.985 and 5.541>1.985. The Performance Expectations have no significant effect with t count is smaller than t table (0.539<1.985) and Social Influence has a negative influence on Behavioral Interest with t count (-0.141<1.985). Meanwhile, simultaneously, the four variables have a significant influence as proven by the f count value that is greater than the f table, which is 38.76>2.47 with a determination coefficient of 0.645. It means that all four aspects influence the Behavioral Interest by 65% and the rest are influenced by variables other than the independent variables in this study.